NHS Workshop Introduction to ggplot

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---

# Target Audience

- people with some experience of R, but haven't made the plunge to ggplot. __Just yet__.

- do data analysis in R and provide visualisations using base graphics, or something else.

---

# Why ggplot?

- while some plots can be easier to produce using base graphics

.pull-left[

```r
hist(LOS_model$Age)
```

]

.pull-right[

```r
ggplot(data = LOS_model, aes(Age)) +
  geom_histogram()
```

]

---

# Why ggplot?

- anything moderately complicated is better in ggplot

.pull-left[

```r
# David Robinson
# http://varianceexplained.org/r/why-I-use-ggplot2/
par(mar = c(1.5, 1.5, 1.5, 1.5))

colors <- 1:6
names(colors) <- unique(top_data$nutrient)

# legend approach from http://stackoverflow.com/a/10391001/712603
m <- matrix(c(1:20, 21, 21, 21, 21), nrow = 6, ncol = 4, byrow = TRUE)
layout(mat = m, heights = c(.18, .18, .18, .18, .18, .1))

top_data$combined <- paste(top_data$name, top_data$systematic_name)
for (gene in unique(top_data$combined)) {
 sub_data <- filter(top_data, combined == gene)
 plot(expression ~ rate, sub_data, col = colors[sub_data$nutrient], main = gene)
 for (n in unique(sub_data$nutrient)) {
 m <- lm(expression ~ rate, filter(sub_data, nutrient == n))
 if (!is.na(m$coefficients[2])) {
 abline(m, col = colors[n])
 }
 }
}

# create a new plot for legend
plot(1, type = "n", axes = FALSE, xlab = "", ylab = "")
legend("top", names(colors), col = colors, horiz = TRUE, lwd = 4)
```
]

.pull-right[
![](data:image/png;base64,#day-01-basics_files/figure-html/baseplot-label-out-1.png)
]

---

# Why ggplot?

- anything moderately complicated is better in ggplot

.pull-left[

```r
ggplot(top_data, aes(rate, expression, color = nutrient)) +
    geom_point(show.legend = FALSE) +
    geom_smooth(method = "lm", se = FALSE, show.legend = FALSE) +
    facet_wrap(~systematic_name, scales = "free_y")
```
]

.pull-right[
![](data:image/png;base64,#day-01-basics_files/figure-html/ggplot-label-out-1.png)
]

---

# Lots of addin packages for ggplot

gg.gap, ggallin, ggalluvial, ggalt, ggamma, gganimate, ggasym, ggbeeswarm, ggBubbles, ggbuildr, ggbump, ggcharts, ggChernoff, ggconf, ggcorrplot, ggdag, ggdark, ggDCA, ggdemetra, ggdendro, ggdist, ggdmc, gge, ggeasy, ggedit, ggeffects, ggenealogy, ggetho, ggExtra, ggfan, ggfittext, ggfocus, ggforce, ggformula, ggfortify, gggap, gggenes, ggghost, gggibbous, ggguitar, gghalfnorm, gghalves, gghighlight, ggimage, ggimg, gginference, gginnards, ggip, ggiraph, ggiraphExtra, ggjoy, gglasso, gglm, gglogo, ggloop, gglorenz, ggm, ggmap, ggmcmc, ggmix, ggmosaic, ggmr, ggmsa, ggmuller, ggmulti, ggnetwork, ggnewscale, ggnormalviolin, ggnuplot, ggpacman, ggpage, ggparallel, ggparliament, ggparty, ggperiodic, ggplot.multistats, ggplot2, ggplot2movies, ggplotAssist, ggplotgui, ggplotify, ggplotlyExtra, ggpmisc, ggPMX, ggpointdensity, ggpol, ggpolypath, ggpubr, ggpval, ggQC, ggQQunif, ggquickeda, ggquiver, ggRandomForests, ggraph, ggraptR, ggrasp, ggrastr, ggrepel, ggResidpanel, ggridges, ggrisk, ggROC, ggroups, ggsci, ggseas, ggseqlogo, ggsignif, ggsn, ggsoccer, ggsolvencyii, ggsom, ggspatial, ggspectra, ggstance, ggstar, ggstatsplot, ggstudent, ggswissmaps, ggtern, ggtext, ggThemeAssist, ggthemes, ggTimeSeries, ggupset, ggVennDiagram, ggversa, ggvis, ggvoronoi, ggwordcloud

---

# And others, that make ggplots that can then be modified and treated as such

.pull-left[

```r
fviz_cluster_example
```

![](data:image/png;base64,#day-01-basics_files/figure-html/unnamed-chunk-4-1.png)
]

.pull-right[

```r
fviz_cluster_example + theme_classic()
```

![](data:image/png;base64,#day-01-basics_files/figure-html/unnamed-chunk-5-1.png)
]